CN116882724A - Method, device, equipment and medium for generating business process optimization scheme - Google Patents
Method, device, equipment and medium for generating business process optimization scheme Download PDFInfo
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Abstract
The invention discloses a method, a device, equipment and a medium for generating a business process optimization scheme. The method comprises the following steps: acquiring a full call chain log corresponding to a target platform, and preprocessing the full call chain log according to a target service class to obtain a basic call chain log; determining a target call chain log in a basic call chain according to the target serial number, and constructing a target service model according to the target call chain log; analyzing and processing a full target business model matched with a full target serial number corresponding to a target business class to obtain bottleneck information of a target platform under the target business class; the bottleneck information comprises bottleneck nodes and bottleneck paths; and determining a target optimization scheme of the target platform under the target service class according to the bottleneck node and the bottleneck path. By the technical scheme, the performance analysis and bottleneck discovery of the service flow can be realized, and the operation efficiency of the service flow is improved.
Description
Technical Field
The present invention relates to the field of process optimization technologies, and in particular, to a method, an apparatus, a device, and a medium for generating a business process optimization scheme.
Background
With the advent of digital wave, the traffic of each platform gradually increased, and it becomes very important to perform process maintenance on the background of each platform. In the prior art, process mining techniques are commonly employed to discover, monitor and improve the actual business processes by extracting ready knowledge from the event logs of the information system.
Currently, common flow mining schemes include Application performance monitoring (Application PerformanceMonitoring, APM) and distributed tracking systems (distributed tracking). The APM is a widely applied service chain bottleneck analysis scheme, and by monitoring and collecting performance data of application programs, including indexes such as response time, throughput, error rate and the like, the APM can automatically track a path and a call chain of a request, identify potential bottlenecks and performance problems, provide visual reporting and analysis tools, and help developers and operation and maintenance personnel locate and solve the bottlenecks. The distributed tracking system is a scheme for analyzing and optimizing the performance of the distributed system, and by adding unique tracking identification (IdentityDocument, ID) to the request and transmitting the unique tracking identification between the services, recording call chain information of the request, the flow and path of the request in the system can be tracked, a visual call chain map is provided, and the identification of bottlenecks and performance problems is facilitated and optimization is performed.
However, as the complexity of the business process increases, the actual process is generally different from the current recording process of the platform, if the existing APM and the distributed tracking system are used for process mining, a great amount of manpower and time are consumed, and the existing process is not fully and accurately perceived and understood, so that the process optimization is not practical, and the optimization scheme corresponding to the process is difficult to accurately obtain. Therefore, how to quickly and accurately realize performance analysis and bottleneck discovery of the service flow and improve the operation efficiency of the service flow is a problem to be solved at present.
Disclosure of Invention
The invention provides a method, a device, equipment and a medium for generating a business process optimization scheme, which can solve the problems of low efficiency and accuracy in performance analysis and bottleneck discovery of a business process.
According to an aspect of the present invention, there is provided a method for generating a business process optimization scheme, including:
acquiring a full call chain log corresponding to a target platform, and preprocessing the full call chain log according to a target service class to obtain a basic call chain log;
determining a target call chain log in a basic call chain according to a target serial number, and constructing a target service model according to the target call chain log;
analyzing and processing a full target business model matched with the full target serial number corresponding to the target business category to obtain bottleneck information of the target platform under the target business category; the bottleneck information comprises bottleneck nodes and bottleneck paths;
and determining a target optimization scheme of the target platform under the target service class according to the bottleneck node and the bottleneck path.
According to another aspect of the present invention, there is provided a device for generating a business process optimization scheme, including:
the log preprocessing module is used for acquiring a full call chain log corresponding to the target platform, preprocessing the full call chain log according to the target service class, and obtaining a basic call chain log;
the model construction module is used for determining a target call chain log in the basic call chain according to the target serial number and constructing a target service model according to the target call chain log;
the model analysis module is used for analyzing and processing a full target service model matched with the full target serial number corresponding to the target service class to obtain bottleneck information of the target platform under the target service class; the bottleneck information comprises bottleneck nodes and bottleneck paths;
and the scheme determining module is used for determining a target optimization scheme of the target platform under the target service class according to the bottleneck node and the bottleneck path.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of generating a business process optimization scheme according to any of the embodiments of the present invention.
According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to implement a method for generating a business process optimization scheme according to any embodiment of the present invention when executed.
According to the technical scheme, the full-quantity call chain logs corresponding to the target platform are obtained, the full-quantity call chain logs are preprocessed according to the target service types to obtain the basic call chain logs, then the target call chain logs in the basic call chain are determined according to the target serial numbers, the target service model is built according to the target call chain logs, then the full-quantity target service model matched with the full-quantity target serial numbers corresponding to the target service types is analyzed and processed to obtain bottleneck information of the target platform under the target service types, and finally the target optimization scheme of the target platform under the target service types is determined according to bottleneck nodes and bottleneck paths in the bottleneck information, so that the problems of low efficiency and accuracy of performance analysis and bottleneck discovery of the service flows in the prior art are solved, the performance analysis and bottleneck discovery of the service flows can be rapidly and accurately achieved, and the operation efficiency of the service flows is improved.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for generating a business process optimization scheme according to a first embodiment of the present invention;
FIG. 2 is a flowchart of a method for generating a business process optimization scheme according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a generating device of a business process optimization scheme according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device implementing a method for generating a business process optimization scheme according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "target," "base," and the like in the description and claims of the present invention and the above-described drawings are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
Fig. 1 is a flowchart of a method for generating a business process optimization scheme according to a first embodiment of the present invention, where the method may be performed by a device for generating a business process optimization scheme, the device for generating a business process optimization scheme may be implemented in hardware and/or software, and the device for generating a business process optimization scheme may be configured in an electronic device. As shown in fig. 1, the method includes:
s110, acquiring a full call chain log corresponding to the target platform, and preprocessing the full call chain log according to the target service class to obtain a basic call chain log.
The target platform may refer to a background with a business process function. By way of example, an e-commerce platform may be provided. Call chain logs may refer to logs that record the execution of business processes. The call chain log of each service record contains information such as a service serial number, a service name, call time and the like. The full call chain log may refer to call chain logs corresponding to all business processes in the target platform.
The service class may refer to a job type of the service flow. Different business processes typically correspond to different business categories. The service class may be an order class, a registration class, or the like, which is not limited by the embodiment of the present invention. The target traffic class may refer to a traffic class corresponding to a traffic flow for which flow optimization is required.
The basic call chain log may refer to a call chain log obtained by preprocessing a full call chain log by using a target service class.
S120, determining a target call chain log in a basic call chain according to the target serial number, and constructing a target service model according to the target call chain log.
The target serial number may refer to a serial number of a service corresponding to the service flow selected for flow optimization. For example, assuming that the target platform is an e-commerce platform, after the user executes the service flow of the order-placing category, a unique service flow number is generated and transmitted in the whole call chain. The target call chain log may refer to a call chain log that matches the target serial number.
The target business model may refer to a business process model that converts information in a target call chain log into an activity of a business process.
Notably, by constructing the target service model by using the call chain log, the service serial number can be ensured to be accurately transmitted in the whole call chain, and can be used as a keyword to track in the call chain log, so that related events can be associated more accurately, and an effective foundation is provided for constructing the service flow model with the service context relation.
S130, analyzing and processing a full target business model matched with the full target serial number corresponding to the target business category to obtain bottleneck information of the target platform under the target business category; the bottleneck information comprises bottleneck nodes and bottleneck paths.
The bottleneck information may refer to information required to be improved by the business process of the target business class in the target platform. Typically, the bottleneck information includes bottleneck nodes and bottleneck paths.
The bottleneck node may refer to a flow node of the business flow of the target business class, which needs to be improved. Illustratively, the business process of the order category may be: logging in, ordering and paying, the bottleneck node may be the ordering node. The bottleneck path may refer to a generated path corresponding to the bottleneck node. For example, if the bottleneck node is an ordering node, the bottleneck path may be an operation page for the user to perform the ordering operation. In general, bottleneck paths corresponding to the same bottleneck node in a business process of the same target business class may be different.
And S140, determining a target optimization scheme of the target platform under the target service class according to the bottleneck node and the bottleneck path.
The target optimization scheme may refer to a scheme for optimizing a business process of a target business class in the target platform. By way of example, the target optimization scheme may be to add server resources, optimize database queries, introduce caching mechanisms, etc.
In an optional embodiment, after determining the target optimization scheme of the target platform under the target traffic class according to the bottleneck node and the bottleneck path, the method further includes: and carrying out optimization and improvement treatment on the target platform according to the target optimization scheme.
Specifically, after determining the target optimization scheme corresponding to the service flow of the target service class in the target platform, the corresponding optimization measure can be executed according to the target optimization scheme, so as to optimize and improve the service flow of the target service class in the target platform, and improve the operation efficiency of the service flow.
According to the technical scheme, the full-quantity call chain logs corresponding to the target platform are obtained, the full-quantity call chain logs are preprocessed according to the target service types to obtain the basic call chain logs, then the target call chain logs in the basic call chain are determined according to the target serial numbers, the target service model is built according to the target call chain logs, then the full-quantity target service model matched with the full-quantity target serial numbers corresponding to the target service types is analyzed and processed to obtain bottleneck information of the target platform under the target service types, and finally the target optimization scheme of the target platform under the target service types is determined according to bottleneck nodes and bottleneck paths in the bottleneck information, so that the problems of low efficiency and accuracy of performance analysis and bottleneck discovery of the service flows in the prior art are solved, the performance analysis and bottleneck discovery of the service flows can be rapidly and accurately achieved, and the operation efficiency of the service flows is improved.
Example two
Fig. 2 is a flowchart of a method for generating a service flow optimization scheme according to a second embodiment of the present invention, where the method is based on the foregoing embodiment, and in this embodiment, specifically, the operation of preprocessing the full call chain log according to a target service class to obtain a base call chain log is refined, and may specifically include: analyzing and processing the full call chain log corresponding to the target platform to obtain a full analysis log containing each business class; and screening and processing the full-volume analysis log according to the target business category to obtain a basic call chain log. As shown in fig. 2, the method includes:
s210, acquiring a full call chain log corresponding to the target platform.
S220, analyzing and processing the full-volume call chain log corresponding to the target platform to obtain a full-volume analysis log containing each business class.
The full-volume analysis log may refer to log content obtained by performing log analysis processing on the full-volume call chain log.
Specifically, the log analysis processing is performed on the full call chain log corresponding to the target platform, so that the full analysis log can be obtained, and the service class corresponding to each full analysis log can be determined.
S230, screening and processing the full-volume analysis log according to the target business category to obtain a basic call chain log.
Specifically, after obtaining the full-volume analysis log containing each service category, the target service category can be utilized to screen out a basic call chain log matched with the service category in the full-volume analysis log, thereby providing an effective basis for the subsequent determination of the optimization scheme.
It should be noted that, because the formats of the call chain logs recorded by different servers are different, after the base call chain log is obtained, the base call chain log can be further converted into a fixed format so as to facilitate subsequent analysis and processing.
S240, determining a target call chain log in the basic call chain according to the target serial number, wherein the target call chain log comprises the target serial number and a target call link port name.
The name of the target call link port may refer to a call link span (span) interface name of a business process of a target business class in the target platform. In general, after the call chain log is analyzed, the service serial number and the call link port name contained in the call chain log can be determined.
Specifically, after the basic call chain log is obtained, the target call chain log with the service serial number consistent with the target serial number in the basic call chain log can be screened out according to the target serial number, so that an effective basis is provided for subsequent analysis processing.
S250, obtaining a target call link port name in a target call link log, and constructing a target service model according to the target call link port name.
Specifically, after determining the target call link log according to the target serial number, the name of the target call link port in the target call link log can be used as the activity of the service flow, and a target service model of the service flow can be constructed. In the embodiment of the invention, the target service model may be a PetriNet model.
For example, if the name of the target call link port in the target call link log corresponding to the target serial number a is [ login, ordering, payment ], the name of the target serial number and the name of the target call link port are converted into the activity of the service flow, and then the target service model can be constructed and obtained: - - (login) - - > [ P1] - - (order) - - > [ P2] - - (payment) - - >. Wherein P1 and P2 may represent location points in the target service model, which are not specifically explained in the embodiment of the present invention.
And S260, simulating and running the full-quantity target service models according to the target analysis tool to obtain target libraries and target transitions corresponding to the full-quantity target service models.
Wherein the target analysis tool may refer to a pre-selected model analysis tool. By way of example, it may be a time arc Petri network authentication tool (ToolforVertification time-ArcPetri Net, tapaal) or a coloring Petri network (ColoredPetrinets, CPN) authentication tool, etc.
Wherein the target repository may refer to elements in the target business model that represent locations. In general, circles can be used to represent the Petri Net model. Target transitions may refer to elements in the target business model that represent transitions. Typically, this can be represented by a short line in the petnet model.
S270, analyzing and processing target library and target transition corresponding to each full target service model according to a target analysis tool to obtain bottleneck information of the target platform under the target service class; the bottleneck information comprises bottleneck nodes and bottleneck paths.
Specifically, the bottleneck nodes and bottleneck paths of the business processes corresponding to the target business categories can be identified by analyzing and processing target libraries and target transitions in all the full-scale target business models through a target analysis tool.
Illustratively, the target business model is modeled by the Tapaal tool: analysis of- - (login) - - > [ P1] - - (order) - - > [ P2] - - (payment) - - >, finds that there is a large resource solicitation between the library of "order" activities and the transition, so the "order" activities can be used as bottleneck nodes of the business process.
S280, acquiring a matched basic optimization scheme in a preset database according to the bottleneck node and the bottleneck path, and taking the basic optimization scheme as a target optimization scheme of the target platform under the target business category.
Specifically, after the bottleneck nodes and the bottleneck paths are determined, the matched basic optimization scheme can be screened out from the preset database and used as a target optimization scheme of the business process.
In an optional embodiment, before determining the target optimization scheme of the target platform under the target traffic class according to the bottleneck node and the bottleneck path, the method further includes: and generating a basic optimization scheme corresponding to each business category according to the total business category and the historical optimization strategy corresponding to the target platform, and storing the basic optimization scheme into a preset database.
The historical optimization strategy may refer to an optimization scheme existing in the historical data. The basic optimization scheme may refer to an optimization scheme that matches each traffic class. For example, probability screening operation may be performed on the historical optimization policy, so as to determine a basic optimization scheme corresponding to each service class. The preset database may refer to a preset storage database.
Specifically, the basic optimization schemes corresponding to the business categories are generated through the historical optimization strategies and stored, so that after bottleneck nodes and bottleneck paths corresponding to the business processes are determined, the corresponding target optimization schemes can be quickly and accurately matched, and the optimization efficiency of the business processes is improved.
According to the technical scheme, a full-quantity analysis log corresponding to a target platform is analyzed and processed to obtain a full-quantity analysis log containing each service type, the full-quantity analysis log is screened and processed according to the target service types to obtain a basic call chain log, further, the target call chain log in the basic call chain is determined according to a target serial number, wherein the target call chain log contains a target serial number and a target call link port name, a target service model is built according to the target call link port name in the target call chain log, further, the full-quantity target service model is simulated and operated according to a target analysis tool to obtain target libraries and target transitions corresponding to the full-quantity target service models, and the target libraries and the target transitions corresponding to the full-quantity target service models are analyzed and processed according to the target analysis tool to obtain bottleneck information of the target platform under the target service types; and finally, acquiring a matched basic optimization scheme in a preset database according to the bottleneck nodes and the bottleneck paths, and taking the basic optimization scheme as a target optimization scheme of a target platform under a target service class, so that the problems of low efficiency and accuracy of performance analysis and bottleneck discovery of the service flow in the prior art are solved, the performance analysis and bottleneck discovery of the service flow can be rapidly and accurately realized, and the operation efficiency of the service flow is improved.
On the basis of the above embodiment, if the target platform is a run-to-run service platform, determining a target optimization scheme of the target platform under the target service class according to the bottleneck node and the bottleneck path includes: and checking the overtime condition of the bottleneck node under the target service class according to the consistency, and acquiring a matched basic optimization scheme in a preset database according to the overtime condition to serve as a target optimization scheme of the target platform under the target service class. Specifically, the embodiment of the invention can also collect the full call chain logs of the batch service platform at night, preprocess the full call chain logs according to the target service class to obtain the basic call chain logs, then determine the target call chain logs in the basic call chain according to the target serial numbers, construct the target service model according to the target call chain logs, and further analyze and process the full target service model matched with the full target serial numbers corresponding to the target service class to obtain bottleneck information of the target platform under the target service class; and finally, checking the overtime condition of the processing task of the bottleneck node of the service flow under the target service class through consistency, and early warning the condition of insufficient subsequent time in advance, thereby calling the optimization plan in advance. The optimization scheme may include adjustment of resource allocation, optimization of concurrency performance, reconstruction of bottleneck paths, and the like. Thus, the delay of the business process can be reduced, and the response speed can be improved.
Example III
Fig. 3 is a schematic structural diagram of a generating device of a business process optimization scheme according to a third embodiment of the present invention. As shown in fig. 3, the apparatus includes: a log preprocessing module 310, a model construction module 320, a model analysis module 330, and a scheme determination module 340;
the log preprocessing module 310 is configured to obtain a full call chain log corresponding to the target platform, and preprocess the full call chain log according to the target service class to obtain a basic call chain log;
the model building module 320 is configured to determine a target call chain log in a basic call chain according to a target serial number, and build a target service model according to the target call chain log;
the model analysis module 330 is configured to analyze and process a full-scale target service model matched with a full-scale target serial number corresponding to the target service class, so as to obtain bottleneck information of the target platform under the target service class; the bottleneck information comprises bottleneck nodes and bottleneck paths;
the solution determining module 340 is configured to determine a target optimization solution of the target platform under the target service class according to the bottleneck node and the bottleneck path.
According to the technical scheme, the full-quantity call chain logs corresponding to the target platform are obtained, the full-quantity call chain logs are preprocessed according to the target service types to obtain the basic call chain logs, then the target call chain logs in the basic call chain are determined according to the target serial numbers, the target service model is built according to the target call chain logs, then the full-quantity target service model matched with the full-quantity target serial numbers corresponding to the target service types is analyzed and processed to obtain bottleneck information of the target platform under the target service types, and finally the target optimization scheme of the target platform under the target service types is determined according to bottleneck nodes and bottleneck paths in the bottleneck information, so that the problems of low efficiency and accuracy of performance analysis and bottleneck discovery of the service flows in the prior art are solved, the performance analysis and bottleneck discovery of the service flows can be rapidly and accurately achieved, and the operation efficiency of the service flows is improved.
Optionally, the log preprocessing module 310 may specifically be configured to:
analyzing and processing the full call chain log corresponding to the target platform to obtain a full analysis log containing each business class;
and screening and processing the full-volume analysis log according to the target business category to obtain a basic call chain log.
Optionally, the target call link log includes a target serial number and a target call link port name;
the model building module 320 may specifically be configured to: and obtaining a target call link port name in a target call link log, and constructing a target service model according to the target call link port name.
Optionally, the model analysis module 330 may specifically be configured to:
according to the target analysis tool, the full-volume target service models are simulated and operated, and target library and target transition corresponding to each full-volume target service model are obtained;
and analyzing and processing target library and target transition corresponding to each full target service model according to the target analysis tool to obtain bottleneck information of the target platform under the target service class.
Optionally, the generating device of the business process optimization scheme may further include: and the scheme storage module is used for generating basic optimization schemes corresponding to all business categories according to the total business categories and the historical optimization strategies corresponding to the target platform before determining the target optimization scheme of the target platform under the target business categories according to the bottleneck nodes and the bottleneck paths, and storing the basic optimization schemes into a preset database.
Optionally, the scheme determining module 340 may specifically be configured to: and acquiring a matched basic optimization scheme in a preset database according to the bottleneck nodes and the bottleneck paths, and taking the basic optimization scheme as a target optimization scheme of the target platform under the target service class.
Optionally, the generating device of the business process optimization scheme may further include: and the post-processing module is used for carrying out optimization improvement processing on the target platform according to the target optimization scheme after determining the target optimization scheme of the target platform under the target service class according to the bottleneck node and the bottleneck path.
The device for generating the business process optimization scheme provided by the embodiment of the invention can execute the method for generating the business process optimization scheme provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Example IV
Fig. 4 shows a schematic diagram of an electronic device 410 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 4, the electronic device 410 includes at least one processor 420, and a memory, such as a Read Only Memory (ROM) 430, a Random Access Memory (RAM) 440, etc., communicatively coupled to the at least one processor 420, wherein the memory stores computer programs executable by the at least one processor, and the processor 420 may perform various suitable actions and processes according to the computer programs stored in the Read Only Memory (ROM) 430 or the computer programs loaded from the storage unit 490 into the Random Access Memory (RAM) 440. In RAM440, various programs and data required for the operation of electronic device 410 may also be stored. The processor 420, ROM430, and RAM440 are connected to each other by a bus 450. An input/output (I/O) interface 460 is also connected to bus 450.
Various components in the electronic device 410 are connected to the I/O interface 460, including: an input unit 470 such as a keyboard, a mouse, etc.; an output unit 480 such as various types of displays, speakers, and the like; a storage unit 490, such as a magnetic disk, an optical disk, or the like; and a communication unit 4100, such as a network card, modem, wireless communication transceiver, etc. The communication unit 4100 allows the electronic device 410 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunications networks.
Processor 420 may be a variety of general-purpose and/or special-purpose processing components having processing and computing capabilities. Some examples of processor 420 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 420 performs the various methods and processes described above, such as the method of generating a business process optimization scheme.
The method comprises the following steps:
acquiring a full call chain log corresponding to a target platform, and preprocessing the full call chain log according to a target service class to obtain a basic call chain log;
determining a target call chain log in a basic call chain according to a target serial number, and constructing a target service model according to the target call chain log;
analyzing and processing a full target business model matched with the full target serial number corresponding to the target business category to obtain bottleneck information of the target platform under the target business category; the bottleneck information comprises bottleneck nodes and bottleneck paths;
and determining a target optimization scheme of the target platform under the target service class according to the bottleneck node and the bottleneck path.
In some embodiments, the method of generating a business process optimization scheme can be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as storage unit 490. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 410 via the ROM430 and/or the communication unit 4100. When the computer program is loaded into RAM440 and executed by processor 420, one or more steps of the method of generating a business process optimization scheme described above may be performed. Alternatively, in other embodiments, processor 420 may be configured to perform the method of generating the business process optimization scheme in any other suitable manner (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for carrying out methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (11)
1. The method for generating the business process optimization scheme is characterized by comprising the following steps:
acquiring a full call chain log corresponding to a target platform, and preprocessing the full call chain log according to a target service class to obtain a basic call chain log;
determining a target call chain log in a basic call chain according to a target serial number, and constructing a target service model according to the target call chain log;
analyzing and processing a full target business model matched with the full target serial number corresponding to the target business category to obtain bottleneck information of the target platform under the target business category; the bottleneck information comprises bottleneck nodes and bottleneck paths;
and determining a target optimization scheme of the target platform under the target service class according to the bottleneck node and the bottleneck path.
2. The method of claim 1, wherein preprocessing the full call chain log according to the target traffic class to obtain a base call chain log comprises:
analyzing and processing the full call chain log corresponding to the target platform to obtain a full analysis log containing each business class;
and screening and processing the full-volume analysis log according to the target business category to obtain a basic call chain log.
3. The method of claim 1, wherein the target call chain log comprises a target serial number and a target call link port name;
the constructing a target service model according to the target call chain log comprises the following steps:
and obtaining a target call link port name in a target call link log, and constructing a target service model according to the target call link port name.
4. The method according to claim 1, wherein the analyzing the full-scale target service model matched with the full-scale target serial number corresponding to the target service class to obtain bottleneck information of the target platform under the target service class includes:
according to the target analysis tool, the full-volume target service models are simulated and operated, and target library and target transition corresponding to each full-volume target service model are obtained;
and analyzing and processing target library and target transition corresponding to each full target service model according to the target analysis tool to obtain bottleneck information of the target platform under the target service class.
5. The method of claim 1, further comprising, prior to said determining a target optimization scheme for the target platform under the target traffic class based on the bottleneck node and bottleneck path:
and generating a basic optimization scheme corresponding to each business category according to the total business category and the historical optimization strategy corresponding to the target platform, and storing the basic optimization scheme into a preset database.
6. The method according to claim 5, wherein determining a target optimization scheme of the target platform under the target traffic class according to the bottleneck node and the bottleneck path comprises:
and acquiring a matched basic optimization scheme in a preset database according to the bottleneck nodes and the bottleneck paths, and taking the basic optimization scheme as a target optimization scheme of the target platform under the target service class.
7. The method of claim 1, further comprising, after said determining a target optimization scheme for the target platform under the target traffic class based on the bottleneck node and the bottleneck path:
and carrying out optimization and improvement treatment on the target platform according to the target optimization scheme.
8. The method of claim 5, wherein if the target platform is a run-to-run service platform, the determining a target optimization scheme of the target platform under the target service class according to the bottleneck node and the bottleneck path comprises:
and checking the overtime condition of the bottleneck node under the target service class according to the consistency, and acquiring a matched basic optimization scheme in a preset database according to the overtime condition to serve as a target optimization scheme of the target platform under the target service class.
9. The device for generating the business process optimization scheme is characterized by comprising the following steps:
the log preprocessing module is used for acquiring a full call chain log corresponding to the target platform, preprocessing the full call chain log according to the target service class, and obtaining a basic call chain log;
the model construction module is used for determining a target call chain log in the basic call chain according to the target serial number and constructing a target service model according to the target call chain log;
the model analysis module is used for analyzing and processing a full target service model matched with the full target serial number corresponding to the target service class to obtain bottleneck information of the target platform under the target service class; the bottleneck information comprises bottleneck nodes and bottleneck paths;
and the scheme determining module is used for determining a target optimization scheme of the target platform under the target service class according to the bottleneck node and the bottleneck path.
10. An electronic device, the electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of generating a business process optimization scheme of any one of claims 1-8.
11. A computer readable storage medium storing computer instructions for causing a processor to execute a method of generating a business process optimization scheme according to any one of claims 1-8.
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